import torch

import torch.nn.functional as F

input = torch.tensor([[1, 2, 0, 3, 1],
                      [0, 1, 2, 3, 1],
                      [1, 2, 1, 0, 0],
                      [5, 2, 3, 1, 1],
                      [2, 1, 0, 1, 1]
                      ])

kernel = torch.tensor([[1, 2, 1],
                       [0, 1, 0],
                       [2, 1, 0]
                       ])

print(f"input:{input}, input.size(): {input.size()}, input.shape: {input.shape}")
print(f"kernel:{kernel}, kernel.size(): {kernel.size()}, kernel.shape: {kernel.shape}")

input = torch.reshape(input, (1, 1, 5, 5))
kernel = torch.reshape(kernel, (1, 1, 3, 3))


output = F.conv2d(input, kernel, stride=1)
print(f"output:{output}")

output = F.conv2d(input, kernel, stride=2)
print(f"output:{output}")

output = F.conv2d(input, kernel, stride=1, padding=1)
print(f"output:{output}")
